Worker Responses to Automated Safety Warning Systems in Construction Work Environments: A Review with AI-Assisted Screening

Worker responses to automated safety warning (ASW) systems have been widely examined across construction work environments to improve worker safety. However, the evidence of worker response is fragmented because individual studies only examine different types of ASW systems, hazards, work environments, response measures, and review scopes. Therefore, this review synthesizes evidence on worker responses to ASW systems to guide the evaluation and design of future ASW systems. To support this synthesis, five databases, including Scopus and Web of Science, were searched for articles published between 2015 and 2026. The screening process involved two domain experts and three large language models (LLMs) and resulted in 40 included studies. The review found shorter reaction times, hazard avoidance, and improved situation awareness with some ASW systems. Limited comparisons found that auditory-only warnings produced slower responses than vibrotactile warnings under controlled conditions. The review also found that perceiving or reacting to a warning does not always lead to protective action. Therefore, ASW effectiveness should be evaluated across the full worker response chain rather than by warning perception or reaction time alone. It is suggested that future research should examine protective action, repeated exposure, and ASW performance with real workers under realistic work conditions.